Track 3 · Path · 6 explainers
Architectures
CNNs, recurrent nets, autoencoders, GANs, and skip connections
- 1
Convolutional Neural Networks
How CNNs see and understand images
- 2
Recurrent Neural Networks
How RNNs read and understand sequences
- 3
LSTMs
Gates and memory cells for long sequences
- 4
Autoencoders & VAEs
From compression to generation — standard and variational autoencoders
- 5
GANs
Two networks competing to create
- 6
Skip Connections & ResNets
Residual learning and why deeper networks work